Pulling out important information from big volume of data is what data mining is all about. As for the tools used for data mining, these are for the purpose of evaluating data from different perspective and then, summarize it to useful database library. These tools on the other hand have become computer based applications in an effort to handle growing volume of data. There are instances that others are calling these as knowledge discovery tools.
As an idea, data mining existed even before and what is used as data mining tools were only manual processes. Later on, with the onset of hi-tech and fast computers, increased storage capacities and analytical software tools, automated tools were developed eventually which significantly improved the accuracy of data mining speed, analysis and at the same time, brought down the operation costs.
Such methods for data mining are used in an effort to facilitate major elements such as pull out, convert as well as load data to warehouse system, collecting and handling data in database system, allow concerned personnel to acquire the data, do data analysis as well as data presentation in format that can be interpreted quickly for better decision making. As a matter of fact, these said methods of data mining are being used in order to explore trends, correlations as well as associations in stored data that are based on various relationships like for example classes which is a certain predefined group drawn out and the data within it is searched based on the groups, sequential patterns that is used to help in predicting a certain behavior according to the observed trends in stored data, associations or the simplest relationship between data, clusters or logical correlations used in categorizing the data collected.
Industries that are catering heavily to consumers in financial, retail, sports, entertainment, hospitality and so forth are heavily relying on these methods of data mining to be able to obtain quick answers to questions and improve their business further. The tools help them study the buying patterns of consumers and as a result, be able to plan a strategy that can be made for future sales.
As an example, restaurants might like to study the eating habits of their consumers at different times of the day. The data will then help them to decide on the menu to offer at different parts of the day. With data mining tools, it helps them a lot to draw out a business plan, discount plans, advertising strategy and everything in between to further boosts their operations and sales.
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